EcoPhyloMapper: An r package for integrating geographical ranges, phylogeny and morphology

Abstract

1. Spatial patterns of species richness, phylogenetic and morphological diversity are key to answering many questions in ecology and evolution. Across spatial scales, geographical and environmental features, as well as evolutionary history and phenotypic traits, are thought to play roles in shaping both local species communities and regional assemblages. By examining these geographical patterns, it is possible to infer how different axes of biodiversity influence one another, and how their interaction with abiotic factors has led to the spatial distribution of species assemblages-and their attributes-that we observe in the present. Although there has been interest in this area of research for some time, it has recently become more tractable to include multivariate shape data in such analyses. Shape information has the potential to provide a more direct measure of the functional morphology of species as compared to individual trait measurements and might be more relevant to understanding community composition. However, few tools currently exist to explore geographical patterns of both phylogenetic and shape diversity.2. We present the EcoPhyloMaPPEr r package (EPM) that aims to streamline the handling of geographical range polygons or point occurrences and integration of resulting species metacommunities with phylogenetic trees and morphological shape.3. Geographical maps can be generated that demonstrate spatial patterns in diversity metrics pertaining to phylogenetic similarity, multivariate shape similarity and disparity, and combinations of the two. Patterns of taxonomic, phylogenetic and shape disparity turnover can also be visualized. Biodiversity indices summarized across grid cells can easily be exported to GIS software as well as to other r packages that specialize in community assembly or geospatial statistics. 4. This r package will facilitate the geographical exploration of multivariate shape data in concert with phylogenetic diversity, which will, in turn, support macroecological research exploring how species assemblages are structured.Furthermore, this r package should prove useful across a wide range of macroecological applications that extend beyond the study of morphology.

Linnean shortfall and space‐time patterns in species description of New World coralsnakes (Serpentes: Elapidae)

“…Species richness was calculated as the sum of species co‐occurring in a grid cell. The average dates of species description were also calculated for each cell as the average dates of species whose geographic distribution areas overlap in the cells, and both calculations were performed using the R package EcoPhyloMapper (Title et al., 2022).…”

Geographic patterns of living tetrapod diversity reveal the signature of global diversification dynamics

“…Geographic grid and species richness. For each group, we first produced a hexagonal 100-km-resolution species richness grid using the epm package v1.1.1 (Title et al 2022) in R 4.3.0 (R Core Team 2023), with the polygon distribution data transformed into an equal-area Behrmann projection as input and the 'centroid' approach. The resulting grid contains the information of the species present in each hexagonal cell, and was the base cell grid for all subsequent analyses.…”

‘phyloraster': an R package to calculate measures of endemism and evolutionary diversity for rasters

“…We compared the performance of 'phyloraster' with two packages that have similar functionalities: 'epm' (Title et al 2022) and 'phyloregion' (Daru et al 2020). For the performance comparison, we evaluated the patterns of weighted endemism (WE) and phylogenetic diversity (PD) using a dataset of geographical distribution (presence and absence) of 82 tree frog species of the subfamily Pelodryadinae.…”

“…The importance of these metrics (WE, PD, ED and PE) for conservation is extensively recognized, leading to many studies that investigate macroecological and biogeographical patterns linked with phylogenetic data (Faith et al 2004, Barratt et al 2017, Faith 2018). To explore these research questions, a wide array of existing R packages (http://www.r-project.org), such as ‘phyloregion' (Daru et al 2020), ‘picante' (Kembel et al 2010), and ‘pez' (Pearse et al 2015), offer calculations of evolutionary diversity using a diversity of data structures like vectors, large matrices, sparse matrices, and even presence‐absence rasters – as demonstrated by ‘EcoPhyloMapper' (Title et al 2022). Additionally, there are packages outside the R ecosystem that address these metrics, including ‘Biodiverse' (Laffan et al 2010), ‘SDMToolbox' (http://www.sdmtoolbox.org), and ‘lifemapper' (https://lifemapper.github.io/). However, some of these packages do not efficiently handle large data sets or they take a long time to perform calculations.…”